Against metrics: how measuring performance by numbers backfires
aeon.co
aeon.co
We have known this for a long time, but it is hard to have an alternative system which scales well with huge organizations. For startups and small companies, I could see an informal system working pretty well, but as the company grows to hundreds or thousands of employees, it becomes necessary to standardize and have some kind of metrics used for reporting and evaluations. This will inevitably shift the company's culture towards gaming those metrics.
Somewhat like grading systems in education. High grades don't necessarily mean you will be capable of generating more value to society than average grades or even low grades. And students often become good at improving their grades without that actually adding much value. But there is a correlation. And we don't have many better (non-experimental) alternatives that I'm aware of.
Yes, but that's only the beginning of the story. People gaming metrics is a type of security problem, in that "attackers" try to game the metrics while "defenders" try to make them less game-able by improving the accuracy and precision of how the metrics are gathered so that the final numbers continue to tell a valuable story over time.
The issue isn't that metrics can be gamed; it's that organizations which pride themselves on being data-driven rarely make the investment in hiring blue teams and red teams to defend and attack the metrics. If you appreciate that investing in cyberdefense is key to protecting your company from cybersecurity threats, why can't you appreciate that investing in "metricsecurity" is key to protecting your company from "metricsecurity" threats?
The issue is that many of the most important parts of many organisational activities can't be easily measured through simple metrics at all.
It is difficult, but still possible, to measure technical debt and other "hard" metrics. It is precisely the job of the blue team to deal with that.
You're absolutely right that having a "blue team" is much better than not having one - but it doesn't mean that calling out the reality that many organizational activities can't be easily measured is a "rubbish excuse made by people who don't understand".
Or should they be penalised for wasting 15 minutes?
But say you do wish to incentivize that. You can, if you can track the medium of exchange. Take everyone's phone records, reward short conversations, but disincentivize conversations that are too short ("sorry, not now, bye") or too long (social chatting in place of productivity). If you can cost-effectively put it through some kind of ML classifier that could tell you if the conversations were helpful internal support, personal, etc., then all the better. Translate that into some kind of score and factor it into whatever formula that produces personal KPIs.
Not saying it's easy. Just saying it's possible, and it's realistic if you have a team whose full-time job is to come up with these kinds of solutions.
Assuming you want people to help each other, you need to capture metrics on it. A few years back I had a metric of helping n people in a different department: I kept track of those interactions so I had something to report at the end of the year.
If that was a company-issued, top-down metric, I hope it wasn't defined literally as "helping n people in a different department", because that has enough wiggle room to sail an aircraft carrier through. The difficulty of creating a good metric here comes from the difficulty of defining what exactly does it mean, in company context, to "help other people" - and also what it explicitly doesn't mean.
We know many algos are DESIGNED to be a black box, to be unexplainable. Red team iterates an incredibly effective algorithm that produces the desired outputs (with unseen risk built up as well). Blue team, in order to manage risk, is tasked with .. explaining the unexplainable process? An impossible task.
Is it possible that human/organizational processes can be also unexplainable?
Maybe if you had an organization that was big enough to require several blue teams (a military or government?), then you'd need a metric for blue teams. Such a metric would probably compare the sub-KPIs of each sub-organization that each blue team was responsible for, including metrics on customer satisfaction, and warrant investigation if the metrics went under.
The blue teams can't really game that metric without the entire organization falling over, and if that happened, the executives would be to blame, not the blue team.
It's composed of engineers and they analyze existing processes and create new metrics all day long.
They do worry about their own careers/promotions etc but the group is too small for there really to be any opportunities to "game" anything beyond basic politics.
So the metrics are BS, and the company is really being run by subjective intuition, for which th metrics merely provide an impersonal rationalization.
The role of metrics is to grant visibility. Any policies governing outcomes, e.g. pay bonuses for high metrics, those policies are set and iteratively improved by people working off intuition.
Doesn't mean the metrics are bullshit, just means they're a tool.
Sorta sucks, but that's how it goes. Good execs manage a sufficiently decentralized system, but they still need SOME set of summary numbers.
The very important managers themselves should care about evaluating the metrics they impose, but typical unspoken manager performance metrics include "episodes of dissent" (addressed by discouraging advice), "displays of weakness" (addressed by threats and aggressive attitude), "time management" (addressed by not thinking matters through), and so on.
Because if I'm a C-level or EVP-level person responsible for this type of decision, why would I want to spend money on a team of people fighting against my ability to get a big fat bonus?
Does it? Is it inconceivable that each part works to its own goals and metrics consistent both with its own values and those of the wider organisation?
https://www.nytimes.com/2010/02/04/opinion/04brass.html?page...
Article is from 2010
Microsoft for example, was plagued by divisional infighting: ClearType was sabotaged.
Beyond a certain number of people, absolutely it is.
Trying to group 1000 people together and measure all of them, sure that seems insurmountable for an informal system.
Taking that same group of 1000, splitting them into subgroups of 7 and giving those individual groups their own goals and autonomy to pursue them may again allow for informal performance measurement.
that's because of the lack of trust, and the flow of responsibility and control.
If you structure a company such that the employees themselves has to be responsible for their output in such a way that higher output leads to more money for them, you'd not have this problem. For example, contractors who work on a results basis.
so let that happen. Those who can't can leave, and see how the company actually fairs. When they find that some crucial roles aren't taken and the company starts "failing", then they will surely admit that said role is needed, and reward it accordingly.
But perhaps there are indeed roles that aren't useful, and therefore, actually could've been eliminated but for the stigma - so may be this is the way to go forward.
But what metric would you use to measure output that solves the gamification problem?
Even for contractors or sales people (where you could use the sales volume), this could lead them to favor short term results and compromise the long-term health of the company (e.g. by favoring quick, low-quality solutions by contractors, or selling features that don't yet exist and creating unsustainable roadmaps by sales people).
Maybe the gaming effect would be lessened by that compensation approach, but at a very large scale org, I doubt that it would. Although, it would be interesting to see real life studies of this, in case such practices have already been tried out.
It’s only true if you believe that the average human being is not opportunistic.
I currently work for a company that has been transitioning from being tiny (I was employee #24) to pretty big (we're close to 60 now). One thing I've learned, much to my disappointment, is that once you get past a certain size it gets harder and harder to recruit people worth trusting with that kind of responsibility. The supply of such people is too limited, and they tend to get poached quickly.
>If you structure a company such that the employees themselves has to be responsible for their output in such a way that higher output leads to more money for them
Oh so all you need to do is fairly and reliably measure "output" in an ungameable way? Easy! /s
If your feeling that at 60, imagine what that must feel like..
Prior to that size companies can kind of get by on luck, skill, or the "heroic efforts" of individual contributors to carry them along. Once you hit 50 FTE that approach starts to fail more and fail harder. This is why tons of small businesses flame out when they hit this threshold.
I agree with your point, but I think your scale factors for size are off by orders of magnitude.
That seems like an absurd standard to me. The three largest employers in the world (by number of employees) are 1. The U.S. Department of Defense, 2. The People's Liberation Army (China), and 3. Walmart. Each of these three largest employers in the world has between 2 and 3 million employees, which is much less than your standard of "tens of millions".
EDIT to add: To be fair, the author's book (on which the article is based) mentions the term twice (and twice in the references). Still feels like this is inadequate, though.
https://books.google.com/books?redir_esc=y&id=rgs8DwAAQBAJ&q...
At a deeper (very generalized) level, we've been infected by production line, Deming style, efficiency focus.
If you are handling previously defined routines, great. Optimizing can help you.
As soon as you are working with adding value, be it in code, education, product development, metrics are all premature optimization.
Promote the idea that you can't apply optimization techniques to creative steps and encourage managers to get off the numerical crutches and make value judgments. Takes a better manager but then that's the point anyway, right?
Could you say more about this? I'm trying to form an opinion on this Deming-ism. My impression is that the actual Mr. Deming gave different advice: "Eliminate slogans, exhortations, and targets . . . Eliminate quotas, numbers, numerical goals."
If you've got someone who's been tasked with improving large-scale system outcomes, and they're developing metrics that are meant to be a means to that end, then you might expect them to come up with a well-crafted set of metrics. Of course, you can only expect them to implement those metrics to the extent that they're able to alter the system in a way that allows for collecting them. The best plan in the world isn't worth much if nobody has the power to execute on it.
If, on the other hand, they're being designed by someone whose task was, "We need to be more data-driven; come up with some metrics and give me a dashboard," they're going to do exactly that. No more, no less.
Part of the problem is that, in some[0] cases, all measures are poor.
0: probably many, but it depends on how you count[1]
1: which, for that matter, goes right back to the original problem
For example, I've definitely seen this happen on Agile teams where management makes KPIs based on velocity or ticket flow: Suddenly, lots and lots and lots of waste and technical debt are generated due to implementing unnecessary things. Because unquestioningly implementing tickets as fast as you can increases velocity, while spending time to stop and talk about whether or not something is a good idea, or can be solved in a better way, decreases it.
1: Dilution of responsibility.
Metrics are defined by committee, which in turn answers to another strategic leadership committee. No single person is responsible for failure. Mediocre managers recite the entrenched KPI mantra because it cannot fail.
2: Differentiability.
If you can't measure how well you're performing, you can't tell if you're improving or regressing with any given change. Total revenue or other coarse metrics are so far divorced from any given decision that they can't provide feedback about it. Just like gradient descent needs the underlying neural network to be differentiable, a business strategy needs the performance to be differentiable. KPIs are an attempt at that.
Ultimately, KPIs suck but give a fairly predictable average outcome. Not doing KPIs is a risk that most leadership is unwilling to take. KPIs sit in the same category of concepts as airport theatre security. They're a product of (find something you can measure and try to manipulate that number, no matter how meaningless | something must be done. This solution is something. Something is better then nothing. Therefore let's do this).
There are a lot of assumptions baked into that statement, not least among them: (1) that being unable to put a number on it means you can't tell if you're improving or not; (2) that this all boils down to a number anyway (or a reasonable set of numbers); (3) That such numbers are actually predictive.
There are two primary reasons people complain about metrics in my experience: (1) They're difficult/tedious to get and/or (2) they lead companies to focus on the wrong actions. These would belie the claims you're making. (I can't tell if you're making them personally, or just echoing what you've heard, so I'll argue against the generic theory)
Turn your scenario around: We have a system. Experts in the field agree the system is more likely to cause poor decisions than not. Should we continue the system? (And trying to gather metrics on whether the system works or not is not the solution, because the question at hand is if metrics accurately guide decision-making.)
And regarding your latter paragraph, the answer to "Should we continue the system?" depends on what alternative systems can plausibly be implemented for making the same decisions. If the current system causes poor decisions, but the alternatives are even worse (or there are better alternatives which we are unable to implement), then we should keep the current system.
Yes, the whole system would work better if people could just agree on what best needs to be done, and which activities are useful for achieving these goals, but often they can't. Metrics are a solution to a particular problem - an environment with limited trust and plenty of subjective politics, where any non-metric system for evaluating success and assigning benefits will be gamed as well. There possibly can be other solutions, but "simply" not having that problem isn't a solution.
The devil you know, etc.
So as I've said elsewhere, the problem isn't measurement. The problem is as Deming said "The aim defines the system". Well thought out measures in accordance with clear goals and aims can be valuable. Like anything though, it requires careful consideration and may need to be revised based on outcomes.
You focus on your goal and try and take the best path there. LoC written or test coverages are distractions imho. Trust the skilled talented people you’ve hired as they are motivated to make the correct choices.
From that perspective, any metric oriented organisation might want to have an explicit alignment process that ensures that the metrics continue to capture the desired outcome.
> ...any metric oriented organisation might want to have an explicit alignment process that ensures...
One huge problem, however, is that organizations that are apt to rely on metrics usually aren't sensitive enough to realize that there's more to their use than coming up with a wish-list and then dreaming up bullshit KPI's which are somehow intended "move the needle" towards correct outcomes. And when it doesn't someone just bullshits their way around the failure instead of doing the hard work needed to honestly address mistakes and problems.
That's, I think, what happens a lot in dysfunctional school districts, though many of us might see this comedy of errors show up in orgs with a matrix management structure.
There is no metric that can measure my outcome.
Any system which wants to measure these traits is doomed to fail.
If your presence had any impact, then it can be observed in some quantifiable way. Perhaps it's an increase in customer satisfaction, or a bump in revenue, or an increase in team velocity. All of this can be quantified in some form or another.
I don't think this is correct?
Your work having observable impact and being able to show exactly what observable impact your work had in a quantifiable manner are two very different things.
I feel this is a huge problem at Google, where performance reviews/promotions are supposed to be based on objective measures. If you fix a lot of bugs, the end user might be much happier. However, to quantify exactly happy you need to have some existing infrastructure, and even if you do have that infrastructure, how do you know whether they are happy because of the bugs you fixed or the bugs someone else fixed?
It may be possible but is not really worth the effort for a company to invest in. So, what ends up happening is people (who care about perf/promotions) fight for the projects which will give them the most easily measurable impact, and ignore other things which may well be very important to a project or company but are difficult to measure.
Ideally, your performance should only be rated on things that were actually in your control. Admittedly, I don't know how one would do this though.
Don't let the underwhelming title fool you: it's largely a book on why it can't be done. Austin takes classical principal-agent models and extends it to add a third participant: the client. He then shows that difficult-to-observe work at first improves and then worsens under any metrics regime.
No single metric can be found that will give the desired performance. The basket of metrics that can successfully create the desired outcome is one where the principal has total visibility into the agent's work -- which contradicts the original problem of difficult-to-observe work (ie, anything requiring skill).
For the same reason, I've come to find using Uber exhausting. Why do I care about my 4.75 (was 4.77) rating? I take taxis whenever practical because I don't want to endanger my rating by making too much small talk or not making enough small talk.
Looking at upvoted versus downvoted comments, my impression is that it makes things better overall with some subtle downsides, but it is hard to show this.
When you already know what the response is likely to be (because most people are pandering for karma), it's just as pointless.
If you’ve got more that n=5 things, at a certain point you _need_ metrics to make sense of how things are going. Are we getting our product to customers when they want it (OTD)? Being able to say, yes 90% of the time is very helpful compared to saying “who knows, we don’t do metrics here.”
"Gaming" the workplace is happening with or without metric fixation. At least with metric fixation it's front and centre when it occurs.
Maybe there is some truth in it. But I also feel that you might get a better result if you let humans to figure out what is needed to be done to achieve a goal instead of telling them through a metric.
"The key components of metric fixation are the belief that it is possible – and desirable – to replace professional judgment (acquired through personal experience and talent) with numerical indicators of comparative performance based upon standardised data (metrics)"
Basically, it is a problem of trust. You're trying to replace trust in people with a metric which, in theory, lets you not to have trust in them.
Personally, I think it is a foolish goal. You are effectively replacing the trust in people (which, admittedly, is vague) with trust in the metric (which connection to reality is vague). The vagueness has a reason - reality is complicated.
Why not just tell people what the "broader strategic objective" is, instead of trying to come up with a metric that is an exact (and so necessarily wrong) description of it?
If my broader strategic objective is to cut costs by 15% allow more competitive pricing, the last thing I want is for every individual to define what that means to them and hope the math works out in the end.
That's strange to me, because the former surely seems to be much more difficult than the latter.
Its strategic, specific and measurable (we are at 5% and need to get to 30%) but it doesn't say how. Focus on a specific industry? Launch a new product? Restructure the sales org?
Now on the issue of people gaming metrics, that is a real concern and I typically address it with "counter metrics" intended to protect against gaming. It is not perfect, but it works well enough when you take the time to choose your metrics (and counter metrics) carefully.
So instead of "improve A by 20%" we get "improve A by 20% without impacting B"
From the article:
> In an attempt to staunch the flow of faulty metrics through gaming, cheating and goal diversion, organisations often institute a cascade of rules, even as complying with them further slows down the institution’s functioning and diminishes its efficiency.
Of course, how you get there is anything but simple.
It always boils down to what to measure, how to measure it, and how to deal with gaming that. "Boils down to culture" is just weasel words.
Agreed. If it's measured in a metric, like bugs for every check-in or number of check-ins or numbers of lines of code, then reducing it down to metrics doesn't do anything to achieve the goal of the success of the product.
I'd - cautiously - argue it actually favours success of the individual over success of the product.
Things like targets or published measurements that have no particular purpose in your process improvement cycle are risky because they will change behaviour in undefined ways. You should always avoid them if you can.
Measurements should be taken in order to answer a question. You should avoid taking measurements if you have no questions. Similarly, you should try to measure the minimum that you can that will answer your question. This will minimise the change in behaviour.
Before you can have metrics you need a defined process (because by definition a metric is a measurement that is used to change your defined process). Avoid taking metrics when you are unsure of your existing process. When you change your process as a result of a metric, use measurements to answer the question, "Did we affect things we didn't expect to affect". If the answer is "Yes", then take more measurements to answer the question, "Is this change something we need to do something about".
In this way you will be able to control your process. One last thing. Do not attempt to protect against gaming other than to not measure things. People naturally optimise and will do it whether they are aware of it or not. Simply observe the effect of your measurements and decide if they are what you want. If not, then remove the measurement.
The problem is that a lot of businesses focus hard on metrics and this doesn't translate to a process improvement cycle, rather, it's on a "person improvement" cycle - making raises, bonuses, promotions, etc. dependent on that notion.
A perfect example how this is problematic is in areas like Customer Support, where a number of handled tickets doesn't equate to a good value of the product provided.
In a posit, let's consider there's two Support Agents working on supporting 'X' product for 'Y' company, over the course of a quarter. The product and the company have been around and established for quite some time, so there's no need for semantics on availability pool in this posit. Support Agent 1 works a case that takes 3 months but is a relevantly large product bug that impacts millions of users around the world via the fix.
Support Agent 1's workload, of course, has a considerably smaller queue size due to this. Now, Support Agent 2 keeps picking-up the low-hanging fruit because it's a numbers game and they know this.
What should happen is that management sees the disproportionate numbers and attempts to find out why that is (and/or attempts to automate the low-hanging fruit out of the equation). They should also look at the impact that both of their work had, in overall user-base.
Instead, what more than likely happens, is because Support Agent 1's numbers were so low, this makes Support Agent's Manager's numbers look bad and that goes up the chain. Upper Management, oft, doesn't care for the semantics around numbers, so shit rolls down-hill (as the colloquialism goes) and, now, Support Agent 1 is on "Unsatisfactory/Needs Improvement" for their review cycle, losing raises, bonuses, promotions, etc.
I think that would disenfranchise Support Agent 1.
Since this is a majority American board, consider the wonderful hell that is known as Wal-Mart. From what I understand, it also utilises metrics across the board. If you think on it, can you name a person "happy" to work there? I'd reckon you couldn't. (Again, this is my understanding of it and not anedotal, first-hand experience with the company or anyone who works for it. Aside from Asda, in the UK, Wal-Mart isn't a "thing" here.)
So, more than just being fruitless, if it doesn't go into the process improvement cycle, I'd say it rolls pretty high numbers in damaging the overall morale.
This gets into very complicated discussions. How do you measure productivity? How do you reward good performance? Can you use a reward for good (measured) performance as extrinsic motivation?
Anybody who tells you they have a good way of doing this that will work across a wide range of different tasks is either deluded or lying (or both). Lot's of successful businesses are run by deluded/lying people.
Surely a single number or sign only is insufficient for such broad areas. Much less a predictor based on one of those numbers which is why... measures lie. People lie less often and in a more detectable way.
The tangible results of them can be measured but there are multiple variables affecting it, from politics, through skill, talent and finally luck. If any of those elements fail, you get nothing, despite intangible gains that may provide a long term advantage.
You figure out proxies as best you can. How do you know "customer service" or "innovation" are important, are improving, exist, or are what you think they are, without figuring out a way to measure them? This is precisely the bane of buzzwords. "We focus on innovation here!" but no one can determine what that is or if the company is any good at it.
>The tangible results of them can be measured but there are multiple variables affecting it, from politics, through skill, talent and finally luck.
There are a few comments in this thread that seem to come from the same premise: that measuring is hard because "multiple variables" come into play when you measure things. I hate to break it to you, but those factors are in play whether you are measuring things or not. The purpose of measuring is to minimize the unknowns and reduce variance. All of the variety of factors that are in play in a massive organization are precisely why you need to measure things, not a reason to cast measurement aside.
I guess if the metric was "caught Osama Bin Laden or not", then yeah, I agree.
But who on earth would measure the analyst's productivity just so? Nothing but a strawman.
>The source of the trouble is that when people are judged by performance metrics they are incentivised to do what the metrics measure, and what the metrics measure will be some established goal. But that impedes innovation, which means doing something not yet established, indeed that hasn’t even been tried out.
Why? If a (admittedly weak) metric like "# of paying customers" is used as a goal, how does that "impede innovation"? How are people being stopped from coming up with creative ways to get more customers? Why do we assume the ways in which they improve the metric will be bad, and not innovative?
> But who on earth would measure the analyst's productivity just so? Nothing but a strawman.
Is that much different than measuring LoC, tickets closed, or features implemented? Some features just take time -- sometimes just the research alone to implement something could take a few weeks where literally nothing measurable happens. That's the point: completion metrics aren't useful for larger or open-ended projects. There was no gnatt chart, no schedule for finding Osama bin Laden; similarly you sometimes cannot plan out a large software project from the very start.
This is OT, but if you're interested in understanding this epochal event in American media narrative, there's no one better than Sy Hersh to listen to:
https://www.lrb.co.uk/v37/n10/seymour-m-hersh/the-killing-of...
In a way, I guess it is on topic because it shows how "metric fixation" leads to unjust and dangerous outcomes for the people of the world.
But perhaps you're right. In capitalism, the most common purpose why companies exist is to game the system (i.e. make profit). I don't see why in that case, employees shouldn't try to game the people who game them (i.e. capitalists).
However, in companies that are collectively owned, this becomes less clear.
Unless it has no management there is still a management class with disproportionate decision making power and thus the antagonistic relationship necessary for there ti be a clear case for gaming continues to exist. Humans are really bad at removing hierarchies, to the extent that I would assume any place without hierarchies has them in a harder to notice format.
I'm in the restaurant industry, so my #1 metric is profit (over the long run anyhow). Now, the next metric is sales, since profit is a % of sales. So to get those sales, we're looking at how many new guests are coming through the door, repeat guests, average guest check, etc... After that, it's margins. Sales mixes play into that (relating to COGS), and labour. Now, to determine what we're getting out of our labour, more metrics. How much each server is selling, what products they're selling, how many guests they can serve in a night, etc... For cooks, it's about productivity and consistency.
Anyhow, there's a lot of shit restaurants and workers out there (due to low barrier of entry education-wise), lots of people misinterpret the data, leaving to a feedback loop of shit managers and employees. Often restaurants will focus too much on one of those metrics, leading to places that just gauge guests, or others that entertain guests who are fishing for free shit.
Now, as for metrics in the programming world which probably don't matter, I always hear about lines of code written. Obviously it's easy to game and hard to discern, as code can be too terse or too verbose. Programmers are also usually so far removed from the sales part of the business that there's no objective sales metric to use either. And that's where you need good managers. I'm sure there's a good set of metrics that give some idea of performance, but they need to be interpreted by someone.
And all of this reminds me of stats/economics (what I did in university), where you're bombarded with data and need to interpret it. Like GDP per capita can indicate general well being, but then you adjust it to PPP to get a better metric of quality of life, and add inequality calculations to understand how it affects different segments of the population, and you can go even deeper with specific stats underlining quality of life (amount of disposable income, amount spent on housing, amount spent on entertainment, etc...).
Anyhow, tldr here is that metrics matter, but interpreting them is a skill and makes all the difference.
We don't personally verify a financial advisor is a genius, we look at their annual rate of return.
We trust that if unit tests fail, code isn't good.
We trust the SATs, which are a better and more scalable and fair measure of aptitude than any group of humans I could imagine.
The piece rails against metrics, which often backfire, but doesn't even mention the alternative (trust those in power make any choice they desire with no justification) which also is often abused.
If you want an opinion let's go with mine.
Otherwise let's look at the data.
However as an engineering leader you should not discount the value of qualitative metrics or metrics altogether. I try to only make a decision "from the gut" when there is no other choice and decision must be made. Data is key. How do you know how well your code review culture is thriving if you do not see, across the entire team, metrics reporting the number of open pull requests, how long they are staying open on average, how many comments they're getting, etc? How do you know if one of your engineers is struggling if you're not watching what gets checked in, what code is being rewritten frequently, etc? How do you gain leverage for your team to management if their are no facts, metrics, to back you your arguments?
Just a reminder that you should use metrics. Maybe avoid using them as reward mechanisms and use them as leverage instead.
I don't work for GitPrime but you should definitely check out what they're up to.
Who do we believe?
I didn't suggest using metrics to make anyone accountable but using them as leverage to empower your team.
What would be the point of gaming those metrics? Nobody would profit from lies and if you're checking the providence of your data, in the case of Gitprime your own repository, then identifying a culprit would be rather easy.
And unfortunately, I know of at least one software shop where GitPrime metrics are used as reward mechanisms. They influence performance reviews.
Is this really contrary to commonsense belief? I think most business leaders are very aware of this, however, the alternative is chaos. That's why certain specialist teams are given leeway.
(That's not always the wrong view, either — a key part of this is recognizing what kind of situation you're in and whether you really have the trust and resources to bank on a revolutionary change)
You can only effectively use a lagging indicator–such as time to restore–once you understand the activities that make up the world of restoring service. Does the product have an SOP document? Is there monitoring in place to alert technicians quickly? What is the training level of your employees? Are your employees empowered and engaged? All of these things matter far more than lagging outputs.
Sure, we can disparage lagging indicators all day, but we can't throw them out just because they can be gamed. You have to push deeper and that requires time, process knowledge, and building a healthy working environment.
This is exactly why I believe C-level officers are grossly overpaid. Previous success does not guarantee future success, especially in different industries, hence they don't know some magic formula to make his salary * 1000 in profits for the shareholders anymore than a mid level manager does.
http://www.econtalk.org/jerry-muller-on-the-tyranny-of-metri...
I keep trying to say I would rather have 40% well written tests than 80% crappy tests.
:(
The thing is there is no magical way to measure this. How you define personal experience and talent? From the number of years spent in the industry? It's still back to another metric.
Metrics do matter. Common sense does also matter. Making decisions in a chaotic world is indeed difficult.
The choice isn't between metrics and human intuition, it's between explicit and implicit metrics.
Of course there are bad metrics; to use an example from the article - measuring the output of analysts finding OBL on a binary metric is simply a bad metric. But if we start from there, we can improve it. How many leads do they have at the current time? What stage is each lead at? What intelligence has it generated to this point?
"Measuring and Managing Performance in Organizations"
Has a lot of information about how people react and adapt to setting KPIs, aka "gaming the system".
And guess how those industries did that? Metrics.
Metrics are a simple tool. They are almost worthless by themselves and can even be a detriment. But like any tool, if you pick the right ones and use them right, it's much better than not having the tool. There are tons of ways business processes can improve by analyzing metrics, it's not just an employee productivity stick.
https://www.amazon.com/Fixing-Game-Bubbles-Crashes-Capitalis...